mlsanityData to 14 Oct 2026

Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy

arXiv 2106.16162 ↗First posted 30 Jun 2021cs.CVcited by 4

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Abstract (arXiv)

The progress in Computer Aided Diagnosis (CADx) of Wireless Capsule Endoscopy (WCE) is thwarted by the lack of data. The inadequacy in richly representative healthy and abnormal conditions results in isolated analyses of pathologies, that can not handle realistic multi-pathology scenarios. In this work, we explore how to learn more for free, from limited data through solving a WCE multicentric, multi-pathology classification problem. Learning more implies to learning more than full supervision would allow with the same data. This is done by combining self supervision with full supervision, under multi task learning. Additionally, we draw inspiration from the Human Visual System (HVS) in designing self supervision tasks and investigate if seemingly ineffectual signals within the data itself can be exploited to gain performance, if so, which signals would be better than others. Further, we present our analysis of the high level features as a stepping stone towards more robust multi-pathology CADx in WCE.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 8 of its 31 references that are in the map. First posted on arXiv 30 Jun 2021.

Builds on

8 of 31 references.

References · 8

  1. 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,898
  2. 2017Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semanticscited by 1,358
  3. 2016Cross-stitch Networks for Multi-task Learningcited by 467
  4. 2016UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memorycited by 200
  5. 2017Identifying beneficial task relations for multi-task learning in deep neural networkscited by 59
  6. 2017Multi-Task Learning for Mental Health using Social Media Textcited by 25
  7. 2019Endoscopy artifact detection (EAD 2019) challenge datasetcited by 12
  8. 2016Generic Feature Learning for Wireless Capsule Endoscopy Analysiscited by 5

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Cited by year

Citing papers per year: 2022: 2; 2023: 1; 2024: 0; 2025: 1.

4 papers.

  1. 2023Evaluating clinical diversity and plausibility of synthetic capsule endoscopic imagescited by 7
  2. 2025Does DINOv3 Set a New Medical Vision Standard? Benchmarking 2D and 3D Classification, Segmentation, and Registrationcited by 7
  3. 2022From Labels to Priors in Capsule Endoscopy: A Prior Guided Approach for Improving Generalization with Few Labelscited by 3
  4. 2022Time-based Self-supervised Learning for Wireless Capsule Endoscopycited by 2